Project Summary Individuals with chronic lung disease often have conditions that are very dicult to diagnose without the aid of imaging technology. The gold standard, CT scanning, exposes the patient to ionizing radiation and may be harmful in children. Electrical impedance tomography (EIT) is a noninvasive, non-ionizing functional imaging technique in which electrodes are placed on the surface of the body, and low amplitude, low frequency current is applied on the electrodes. This results in a voltage distribution on the electrodes which can then be measured. From these voltages, an image is formed that re ects the conductivity and/or permittivity distribution within the region of interest. Since EIT is a safe and portable technology with no damaging side e ects, it can be used as needed. This project is part of a long term goal to develop an EIT system for imaging patients with chronic lung disease. The goal of this research is to determine whether electrical impedance tomography can provide a means to obtain quantitative and regional information about the extent and nature of bronchial obstruction in patients with cystic brosis (CF). In particular, EIT will be used to identify regions of obstruction (air trapping) and consolidation comprised of atelectasis and airway occlusion in CF patients, and to correlate these measures with improvements seen after hospitalized treatment for a pulmonary exacerbation. The rst speci c aim is to develop algorithms for quantifying bronchial obstruction and consolidation and to determine their sensitivity and speci city. The algorithms will extract information from EIT images of conductivity and permittivity computed using the D-bar reconstruction algorithm developed by the P.I. Data will be collected during spirometry on CF patients clinically indicated for CT scans and on subjects with healthy lungs, and the sensitivity and speci city of the algorithms will be determined using both the data from the healthy subjects and data calculated from CT VIDA Software. The second speci c aim is to determine whether these algorithms can demonstrate the bene cial e ects of antibiotic treatment for CF patients with an acute PE by correlating changes in quantitative EIT measures with clinical measures known to improve following therapy, with patients serving as their own controls. Regional changes in air trapping and consolidation from pre to post treatment as indicated by the EIT images will be calculated, with subjects serving as their own control.